Protecting Privacy When Releasing Search Results from Medical Document Data

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dc.contributor.authorLi, Xiaobai
dc.contributor.authorQin, Jialun
dc.date.accessioned2017-12-28T01:56:05Z
dc.date.available2017-12-28T01:56:05Z
dc.date.issued2018-01-03
dc.description.abstractHealth information technologies have greatly facilitated sharing of personal health data for secondary use, which is critical to medical and health research. However, there is a growing concern about privacy due to data sharing and publishing. Medical and health data typically contain unstructured text documents, such as clinical narratives, pathology reports, and discharge summaries. This study concerns privacy-preserving extraction, summary, and release of information from medical documents. Existing studies on privacy-preserving data mining and publishing focus mostly on structured data. We propose a novel approach to enable privacy-preserving extract, summarize, query and report patients’ demographic, health and medical information from medical documents. The extracted data is represented in a semi-structured, set-valued data format, which can be stored in a health information system for query and analysis. The privacy preserving mechanism is based on the cutting-edge idea of differential privacy, which offers rigorous privacy guarantee.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2018.475
dc.identifier.isbn978-0-9981331-1-9
dc.identifier.urihttp://hdl.handle.net/10125/50363
dc.language.isoeng
dc.relation.ispartofProceedings of the 51st Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPrivacy, 5G and Economics
dc.subjectprivacy, information extraction, data analytics, HIPAA
dc.titleProtecting Privacy When Releasing Search Results from Medical Document Data
dc.typeConference Paper
dc.type.dcmiText

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